Streaming Agents on Confluent Cloud Quickstart

Build real-time AI agents with Confluent Cloud Streaming Agents. This quickstart includes three hands-on labs:

Prerequisites

Required accounts & credentials:

LLM Provider: AWS Bedrock API keys OR Azure OpenAI keys - or BYOK

Required tools:

Confluent CLI - must be logged in
Docker - for Lab1 & Lab3 data generation only
Git
Terraform
uv
AWS CLI or Azure CLI tools for generating API keys

brew install uv git python && brew tap hashicorp/tap && brew install hashicorp/tap/terraform && brew install --cask confluent-cli docker-desktop && brew install awscli # or azure-cli

Windows:

winget install astral-sh.uv Git.Git Docker.DockerDesktop Hashicorp.Terraform ConfluentInc.Confluent-CLI Python.Python

🚀 Quick Start

1. Clone the repository and navigate to the Quickstart directory:

git clone https://github.com/confluentinc/quickstart-streaming-agents.git
cd quickstart-streaming-agents

2. Auto-generate AWS Bedrock or Azure OpenAI keys:

# Creates API-KEYS-[AWS|AZURE].md and auto-populates them in next step
uv run api-keys create

One command deployment:

uv run deploy

That's it! The script will autofill generated credentials and guide you through setup and deployment of your chosen lab(s).

[!NOTE]

See the Workshop Mode Setup Guide for details about auto-generating API keys and tips for running demo workshops.

Directory Structure

quickstart-streaming-agents/
├── terraform/                          
│   ├── core/                           # Shared Confluent Cloud infra for all labs
│   ├── lab1-tool-calling/              # Lab1-specific infra
│   ├── lab2-vector-search/             # Lab2-specific infra
│   └── lab3-agentic-fleet-management/  # Lab3-specific infra
│   └── lab4-pubsec-fraud-agents        # Lab4-specific infra
├── deploy.py                           # Start here with uv run deploy
└── scripts/                            # Python utilities invoked with uv

Cleanup

# Automated
uv run destroy

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Quickstart Streaming Agents

README